A six-year trend of the healthcare cost of arthritis in a population-based cohort of older women
Bibliographic record
Abstract
ABSTRACT ObjectivesTo examine the trend of the healthcare cost of arthritis in a population-based cohort of older women and to estimate the mean adjusted incremental healthcare costs, and selected percentiles. ApproachThis is a healthcare cost study based on individual-level data. Data included health survey and linked administrative data, from 2003 to 2009, from the Australian Longitudinal Study on Women’s Health. The Medicare Australia datasets include the Pharmaceutical Benefits Scheme (unit record data on claims for government-subsidized prescription medicines) and the Medicare Benefits Schedule (listing of health services subsidized by the Australian Government) datasets; they were the source for all healthcare utilization and cost data in this study. The main outcome measure was the incremental healthcare cost of arthritis (estimated from the Australian Government’s cost perspective) expressed as dollars per person per year. All costs were expressed in 2012 Australian dollars. Regression models were used to estimate the adjusted incremental costs of arthritis. The mean adjusted incremental healthcare cost of arthritis was computed using GLMs with a logarithmic-link function and a gamma distribution for costs. The adjusted incremental costs at the 25th, 50th, 75th, 90th and 95th percentiles were computed using Quantile Regression. These percentiles were chosen because cost data are skewed to the right and it was expected that there would be smaller differences between the lower percentiles but bigger differences between upper adjacent percentiles. ResultsData from 4287 women were included in the analysis. Adjusted incremental healthcare cost of arthritis did not increase significantly from 2003 to 2009. However, there were indications that costs at the lower percentiles decreased slightly over the study period while costs at higher (above 50th) percentiles increased. The estimated median cost was $480 (95% CI: $498 - $759) per person per year in 2009. However, ten percent of women had more than 300% higher cost than the “average person” with arthritis. ConclusionHealthcare cost of arthritis represents a substantial burden. However, considering only overall cost does not provide a detailed picture of expenditure. Our results suggest that higher cost patients had different experiences in arthritis cost over time, compared to patients with lower costs, although overall cost has not increased over time. As healthcare spending is concentrated in the high-cost patients, characterising these patients and formulating initiatives that target them could have a considerable impact on improving care and lowering health expenditure due to arthritis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".